Python人工神经网络学习课程Learn Artificial Neural Network From Scratch in Python

欢迎来到我们将从头开始学习人工神经网络（ANN）的课程！如果您正在寻找一门完整的有关使用ANN进行深度学习的课程，该课程教您使用Python创建神经网络模型所需的一切。
您已找到正确的神经网络课程！

完成本课程后，您将能够：

• 确定可以使用神经网络模型解决的业务问题。
• 对高级神经网络概念有清晰的了解，例如渐变下降，向前和向后传播等。
• 使用Python创建神经网络模型，并能够优化模型调整超参数的能力
• 自信地练习，讨论和理解深度学习概念

Created by Sachin Kafle | Published 4/2021
Duration: 18h 13m | 8 sections | 68 lectures | Video: 1280×720, 44 KHz | 5.8 GB
Genre: eLearning | Language: English + Sub

The MOST in-depth look at neural network theory, and how to code one with pure Python and Numpy

What you’ll learn
Code a neural network from scratch in Python and numpy
Learn the math behind the neural networks
Get a proper understanding of Artificial Neural Networks (ANN) and Deep Learning
Derive the backpropagation rule from first principles
Describe the various terms related to neural networks, such as "activation", "backpropagation" and "feedforward"
Learn to evaluate the neural network models

Requirements
Basic math – some essential parts will be covered in the course itself so to make course beginner friendlyLinear and Logistic RegressionBasic understanding of classification and Regression problems
Description
Welcome to the course where we will learn about Artificial Neural Network (ANN) From Scratch!
If you’re looking for a complete Course on Deep Learning using ANN that teaches you everything you need to create a Neural Network model in Python?
You’ve found the right Neural Network course!
After completing this course you will be able to:
Identify the business problem which can be solved using Neural network Models.
Have a clear understanding of Advanced Neural network concepts such as Gradient Descent, forward and Backward Propagation etc.
Create Neural network models in Python and ability to optimize the model tuning hyper parameters
Confidently practice, discuss and understand Deep Learning concepts